TikTok Shop Sales Scraper: Units Sold, Revenue & Sales Trend

Search TikTok Shop by keyword and get the number most scrapers leave out: how many units each product has actually sold.

Every row carries lifetime units sold, estimated revenue, current price and discount, rating, and the shop behind it. Turn on the sales trend and you also get units sold per day and growth percent — figures TikTok does not publish anywhere, calculated from a daily product history we keep ourselves.

Find what is selling, not just what is listed.

Why Use This Scraper

• Units sold on every product, not just title and price
• Estimated revenue per product, so a niche can be ranked by money rather than listing count
• Units sold per day and growth percent, built from our own daily snapshots
• Sales figures on your first run — you are reading history we recorded before you arrived, not waiting for your own second run to have something to compare against
• Filter out dead listings with a minimum units-sold threshold
• No login, no cookies, no proxy configuration, no captchas to solve

Overview

This actor is for people deciding what to sell, source, or promote on TikTok Shop: product researchers, dropshippers, DTC brands, affiliate creators picking what to push, and agencies building client reports.

You give it product keywords. It returns one row per product, sorted by units sold, with the commercial figures attached. It does not need a proxy, a TikTok account, or any captcha handling.

Output is a flat dataset you can export as JSON, CSV, or Excel.

Supported Inputs

Keyword search

The actor takes product search terms, the same words a shopper would type:

{
  "keywords": ["stanley tumbler", "lash serum", "led strip lights"]
}

Each keyword is searched independently and its results are labelled with the keyword that produced them, so one run can cover several niches and stay sortable afterwards.

Unsupported inputs

• Product URLs. This is a search actor. Paste keywords, not links to individual products.
• Shop or storefront URLs. Searching a brand name usually surfaces that shop's products instead.
• Markets other than the United States. See the FAQ for why.

Use Cases

Audience	What they use it for
Product researchers	Rank a niche by units sold before committing to inventory
Dropshippers	Spot products already moving volume rather than guessing from view counts
DTC brands	Track a competitor's catalogue day over day and read the growth rate
Affiliate creators	Pick proven sellers to promote instead of untested listings
Agencies	Build category reports with real sales figures for client pitches
Sourcing teams	Size a category by estimated revenue per product

How It Works

1. You supply one or more product keywords.
2. The actor searches TikTok Shop US for each keyword, walking as many result pages as you allow and discarding duplicates.
3. Every product is normalised into a flat row: units sold, price and discount, rating, shop, and links.
4. Products below your minimum units-sold threshold are dropped, and the rest are sorted with the best sellers first.
5. Each product is matched against our daily archive to calculate units sold per day and growth percent, then written to your dataset.

Input Configuration

Field	Type	Default	Description
keywords	array of strings	required	Product search terms, for example ["stanley tumbler"]. Each is searched separately.
maxResultsPerKeyword	integer	50	Stop after this many products per keyword.
maxPagesPerKeyword	integer	3	Search pages to walk per keyword. Pages overlap, so page two typically adds about half a page of new products. The walk stops early once a page brings nothing new.
minSoldCount	integer	0	Skip products below this many lifetime units sold. Set to 100 or 500 to see only proven movers.
sortBySales	boolean	true	Return best sellers first instead of TikTok's own search order.
includeSalesTrend	boolean	true	Add units sold per day, growth percent, and first-seen date from our daily history.
trendLookbackDays	integer	7	How far back to compare when calculating the trend. Shorter history is reported honestly in trendWindowDays.

Example: proven sellers in one niche

{
  "keywords": ["creatine"],
  "minSoldCount": 500,
  "maxPagesPerKeyword": 3,
  "sortBySales": true
}

Example: wide sweep across several niches

{
  "keywords": ["lash serum", "shapewear", "car vacuum"],
  "maxResultsPerKeyword": 100,
  "maxPagesPerKeyword": 2,
  "includeSalesTrend": true
}

Output Overview

One row per product. The row carries four groups of data: what the product is, what it costs, how much it has sold, and how fast it is moving. Rows that the archive has no history for still carry every commercial field — only the four trend fields stay empty.

Output Sample

A real row, shortened. Produced by keyword air purifier:

{
  "keyword": "air purifier",
  "productId": "1729418122293055820",
  "title": "ToLife TZ-K2 Air Purifier for Large Rooms (up to 1095 Ft2). PM 2.5 Display, Auto Mode, Timer, HEPA Filter",
  "price": 35.88,
  "originalPrice": 66.99,
  "discount": "46%",
  "currency": "USD",
  "soldCount": 114630,
  "estimatedLifetimeRevenue": 4112924.4,
  "rating": 4.7,
  "shopName": "ToLife US",
  "sellerId": "7495436419788278092",
  "isVerifiedSeller": false,
  "labels": ["Free shipping"],
  "productUrl": "https://www.tiktok.com/shop/pdp/1729418122293055820",
  "imageUrl": "https://p16-oec-general-useast5.ttcdn-us.com/tos-useast5-i-omjb5zjo8w-tx/faca10d28fbf4e38a435e89f415f2dc9~tplv-fhlh96nyum-crop-webp:400:400.webp",
  "unitsSoldInWindow": 114,
  "unitsSoldPerDay": 114,
  "salesGrowthPercent": 0.1,
  "trendWindowDays": 1,
  "firstSeenAt": "2026-08-20T21:09:30.079Z",
  "scrapedAt": "2026-08-21T21:56:20.461Z"
}

trendWindowDays reports the real span the trend covers, so a short one is visible rather than dressed up as a full week. The window widens by a day for every day the product stays in the archive.

Key Output Fields

Sales

Field	Meaning
soldCount	Lifetime units sold, as TikTok reports it
estimatedLifetimeRevenue	soldCount multiplied by the current price
unitsSoldInWindow	Units sold since the comparison snapshot
unitsSoldPerDay	Average daily sales across the observed span
salesGrowthPercent	Percent growth of the lifetime total across that span
trendWindowDays	The real number of days the trend covers
firstSeenAt	When the product entered our history

Pricing

price, originalPrice, discount, currency

Product

productId, title, description, category, labels, productUrl, imageUrl

Seller

shopName, sellerId, isVerifiedSeller, shipsFrom

Quality

rating, reviewCount, keyword, scrapedAt

FAQ

Where does the sales trend come from? TikTok publishes soldCount as a lifetime total and nothing else. There is no trend, no daily rate, no growth figure anywhere in its data. We snapshot every product we see once a day and derive the rest from the differences.

Why is the trend empty on some products? Because we are seeing that product for the first time and have nothing to compare against yet. Its soldCount is there immediately; the trend fields fill in from the next run onward. Products already in our history return their trend on your very first run.

Is estimatedLifetimeRevenue real revenue? No, and the name says so. It multiplies lifetime units by the current price. TikTok publishes no per-sale price history, so sales made at a discount are valued at today's price. Use it to rank, not to account.

Why United States only? The upstream data source documents sixteen markets and we tested all sixteen. Only the US is trustworthy. France errored, Spain and Ireland returned nothing, the UK carried sales figures on ten of thirty-one products, Indonesia and Vietnam write prices with a dot as the thousands separator, and Mexico labels its currency USD while returning peso amounts. Publishing prices wrong by a factor of a thousand would be worse than not offering those markets at all.

Why do two runs return different products? TikTok's own search ordering is not stable. Two runs minutes apart return overlapping but different sets. This is TikTok's behaviour, not a fault in the actor.

Why is reviewCount empty? The review count lives on TikTok's product-detail endpoint, not its search endpoint. The star rating is present.

Do I need a proxy or a TikTok account? No. No login, no cookies, no proxy configuration, and no captchas to solve.

Support

Found a bug or missing a field? Open an issue on the actor's Issues tab and it will be looked at.

Additional Services

Need a different market, a scheduled feed into your own warehouse, or a custom field set? Get in touch through the Issues tab and describe the shape you need.

Explore More Scrapers

Other TikTok actors in this collection cover profiles, videos, hashtags, search, comments, ads, and transcripts. Browse the full list on the publisher profile.

🤖 For AI Agents & LLM Apps

Compact reference for AI agents calling this actor via the Apify MCP server or the Apify API (actor: memo23/tiktok-shop-sales-scraper).

Purpose: TikTok Shop US keyword search returning one row per product with lifetime units sold, estimated revenue, and a sales trend derived from a daily archive maintained by the actor.

Minimal input:

{ "keywords": ["creatine"], "maxResultsPerKeyword": 20, "maxPagesPerKeyword": 1 }

Output: one dataset row per product — keyword, productId, title, description, price, originalPrice, discount, currency, soldCount, estimatedLifetimeRevenue, rating, reviewCount, shopName, sellerId, isVerifiedSeller, shipsFrom, labels, category, productUrl, imageUrl, unitsSoldInWindow, unitsSoldPerDay, salesGrowthPercent, trendWindowDays, firstSeenAt, scrapedAt.

Behaviors an agent should know:

• Always set maxResultsPerKeyword. One search page yields roughly 30 to 45 products and maxPagesPerKeyword multiplies that per keyword.
• Pages overlap heavily; results are deduplicated by productId and the walk stops early when a page adds nothing new.
• US market only. There is no region input, deliberately — see the FAQ.
• unitsSoldPerDay, salesGrowthPercent, unitsSoldInWindow, and trendWindowDays are null for products with no prior history. Check for null rather than assuming.
• estimatedLifetimeRevenue is lifetime units times the current price, an estimate rather than reported revenue.
• Billing: every dataset row is charged. The sales trend is a separate charge that fires only for rows where unitsSoldPerDay is actually populated — an empty trend costs nothing extra.

⚠️ Disclaimer

This Actor accesses publicly available product listings on TikTok Shop for legitimate market-research and business-analysis purposes. It does not log in, bypass authentication, or access private content, seller accounts, or personal data. Use of this Actor must comply with TikTok's Terms of Service and all applicable laws, including data-protection regulations (GDPR, CCPA, etc.). The authors are not responsible for any misuse. Users must:

• Respect rate limits and avoid overloading TikTok's infrastructure
• Not use collected data to violate platform terms
• Not republish collected content in violation of copyright

Unlike most scrapers, this Actor does retain a limited record of what it sees, and it is only honest to say so plainly: for every product returned it stores the product id, title, shop name, price, and units-sold figure once per day. That commercial record is what the sales-trend fields are calculated from. No personal data, no reviewer identities, and no buyer information are stored.

TikTok and TikTok Shop are trademarks of ByteDance Ltd.; this Actor is not affiliated with, endorsed by, or sponsored by TikTok or ByteDance.

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